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Record W2170823824 · doi:10.1177/1367877909359732

Considering the fetish value of EOD robots

2010· article· en· W2170823824 on OpenAlexaff
Ian Roderick

Bibliographic record

VenueInternational Journal of Cultural Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicAnthropology: Ethics, History, Culture
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsRobotValuation (finance)Agency (philosophy)SociologyValue (mathematics)NewspaperSocial robotComputer scienceComputer securityArtificial intelligenceBusinessMedia studiesMobile robotSocial scienceRobot control

Abstract

fetched live from OpenAlex

This article explores how the Explosive Ordnance Disposal (EOD) robot is represented to the mass media by the US military as a ‘life-saving device’. Such descriptions of the EOD robot discursively organize it in relation to other objects and actors, endow them with values and capacities, and ultimately situate them in social action. Drawing from US newspaper articles and Department of Defense press releases, the article highlights how the robot descriptions create a sense of automation and agency on the part of the remote-controlled devices that is actually beyond the technology. It is then argued that the IED-combating robot functions as a kind of fetish. Following Baudrillard, the fetish value of the robot stems not from a misunderstanding of its actual or ‘real’ capacities but rather its positive valuation according to a code of functionality that rests upon the risk-transfer labour of the robot.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.039
Scholarly communication0.0080.010
Open science0.0010.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.431
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2010
Admission routes1
Has abstractyes

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